Minimization of water pumps' electricity usage: A hybrid approach of regression models with optimization
Artikel i vetenskaplig tidskrift, 2018

Due to pervasive deployment of electricity-propelled water-pumps, water distribution systems (WDSs) are energy-intensive technologies which are largely operated and controlled by engineers based on their judgments and discretions. Hence energy efficiency in the water sector is a serious concern. To this end, this study is dedicated to the optimal operation of the WDS which is articulated as minimization of the pumps' energy consumption while maintaining flow, pressure, and tank water levels at a minimum level, also known as pump scheduling problem (PSP). This problem is proved to be NP-hard (i.e. a difficult problem computationally). We therefore develop a hybrid methodology incorporating machine-learning techniques as well as optimization methods to address real-life and large-sized WDSs. Other main contributions of this research are (i) in addition to fixed-speed pumps, the variable-speed pumps are optimally controlled, (ii) and operational rules such as water allocation rules can also be explicitly considered in the methodology. This methodology is tested using a large dataset in which the results are found to be highly promising. This methodology has been coded as a user-friendly software composed of MS-Excel (as a user interface), MS-Access (a database), MATLAB (for machine-learning), GAMS (with CPLEX solver for solving optimization problem) and EPANET (to solve hydraulic models).

Optimization

Variable-speed pump

Water distribution system

Machine-learning

Electricity consumption

Författare

Saeed Asadi Bagloee

University of Melbourne

Mohsen Asadi

University of Saskatchewan

Michael Patriksson

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Expert Systems with Applications

0957-4174 (ISSN)

Vol. 107 222-242

Ämneskategorier

Energiteknik

Beräkningsmatematik

Energisystem

DOI

10.1016/j.eswa.2018.04.027